Method and device for measuring volume of non-contact bulk material pile

Abstract

The invention provides a non-contact bulk material pile volume measurement method and device. The method comprises the following steps: acquiring three-dimensional point cloud data of the top surface of a bulk material pile by using a trinocular vision system; b spline interpolation processing is carried out on the three-dimensional point cloud data, so that a continuous curved surface function about the top surface of the bulk cargo pile is obtained in a horizontal projection domain of the top surface of the bulk cargo pile; and in the horizontal projection domain, carrying out two-dimensional integration on the continuous curved surface function along different coordinate axis directions by adopting a Simpson rule so as to obtain the instantaneous volume of the bulk material pile. According to the technical scheme, the three-dimensional point cloud data are obtained in real time through the trinocular vision system, the complex curved surface is expressed as the continuous function through B-spline interpolation, the Simpson law is adopted for two-dimensional integration in the directions of the first coordinate axis and the second coordinate axis, the instantaneous volume can be continuously output without shutdown, the equipment cost is low, maintenance is easy, and the application range is wide. And efficient and accurate dynamic monitoring of the volume of the bulk material pile is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of grain storage management, and particularly relates to a non-contact bulk material pile volume measurement method and device. BACKGROUND

[0002] In a bulk material storage site, the top of the storage pile continuously forms a complex curved surface due to the in-out material operation. The existing technology usually simplifies the curved surface into a regular geometry such as a cone or a prism, or uses laser scanning, voxel accumulation, and binocular / trinocular point cloud combination to estimate the volume by simple integration. However, the former has large errors and cannot reflect the actual undulation; the latter can obtain point clouds, but still uses fixed resolution or cylindrical shell approximation integration, and the curved surface modeling precision is insufficient, and the boundary and recessed area error is amplified. SUMMARY

[0003] The present application provides a non-contact bulk material pile volume measurement method and device, aiming to solve the problems of low bulk material pile volume measurement precision, high equipment cost, and inability to continuously and dynamically monitor in the prior art. Three-dimensional point cloud data of the top surface of the bulk material pile is obtained in real time by a trinocular vision system, a complex curved surface is expressed as a continuous function by B-spline interpolation, so as to accurately describe the shape of the top surface of the bulk material pile of any complexity, and the instantaneous volume is calculated by Simpson's rule two-dimensional integration along different directions, so that the instantaneous volume can be continuously output without stopping, and efficient and accurate dynamic monitoring of the bulk material pile volume is realized.

[0004] In a first aspect, an embodiment of the present application provides a non-contact bulk material pile volume measurement method, which comprises: obtaining three-dimensional point cloud data of the top surface of the bulk material pile by using a trinocular vision system; performing B-spline interpolation processing on the three-dimensional point cloud data to obtain a continuous curved surface function about the top surface of the bulk material pile in a horizontal projection domain of the top surface of the bulk material pile; and performing two-dimensional integration on the continuous curved surface function by using Simpson's rule along different coordinate axis directions in the horizontal projection domain, so as to obtain the instantaneous volume of the bulk material pile, wherein the different coordinate axis directions include a first coordinate axis direction and a second coordinate axis direction, and the first coordinate axis direction and the second coordinate axis direction are perpendicular to each other in the horizontal projection domain.

[0005] In a second aspect, an embodiment of the present application provides a non-contact bulk material pile volume measurement device, which comprises three camera devices and a master control device. The three camera devices are used to construct a trinocular vision system. The master control device is communicatively connected to the three camera devices and comprises a memory and a processor. The memory is used to store a computer program. The processor is used to execute the computer program to realize the non-contact bulk material pile volume measurement method.

[0006] The advantages of the aforementioned non-contact bulk material pile volume measurement method and device are as follows: Real-time image acquisition and generation of three-dimensional point cloud data via a tri-vision system enables continuous dynamic monitoring of volume changes during material feeding and discharging, overcoming the limitations of traditional methods that require machine shutdown for measurement; B-spline interpolation is used to express complex surfaces as continuous functions, significantly improving the ability to describe boundaries and concave regions and avoiding errors caused by simplification of regular geometry; Simpson's rule-based two-dimensional integral is applied along the first and second coordinate axes, further improving the accuracy of volume calculation and making the results closer to the true value; This scheme uses only three camera devices, significantly reducing hardware costs, and the system has no moving parts, making maintenance easier in dusty environments. Overall, it achieves low-cost, high-precision, and easy-to-maintain dynamic monitoring of bulk material pile volume. Attached Figure Description

[0007] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0008] Figure 1 A flowchart illustrating a non-contact bulk material pile volume measurement method provided in an embodiment of this application.

[0009] Figure 2 A flowchart of step S101 provided for an embodiment of this application.

[0010] Figure 3 A flowchart of sub-step S1013 provided for embodiments of this application.

[0011] Figure 4 A flowchart of sub-step S1014 provided for embodiments of this application.

[0012] Figure 5 A flowchart of step S102 provided in the embodiments of this application.

[0013] Figure 6 A flowchart of step S1022, which is provided for an embodiment of this application.

[0014] Figure 7 A flowchart of step S103 provided in the embodiments of this application.

[0015] Figure 8 This is a schematic diagram illustrating an application scenario of the measurement method provided in the embodiments of this application.

[0016] Figure 9This is a schematic diagram of a Simpson integral unit provided in an embodiment of this application.

[0017] Figure 10 A structural block diagram of a non-contact bulk material pile volume measuring device provided in an embodiment of this application.

[0018] Figure 11 This is a schematic diagram of the internal structure of the main control device provided in the embodiments of this application.

[0019] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0021] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar planned objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data are interchangeable where appropriate; in other words, the described embodiments are implemented according to a sequence other than that illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, may also include other content; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0022] It should be noted that the use of terms such as "first" and "second" in this application is for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" and "second" may explicitly or implicitly include one or more of that feature. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0023] In existing technologies, complex curved surfaces are constantly formed on the top of storage piles (such as grain, ore, and feed) due to loading and unloading operations. Existing technologies often simplify these surfaces to regular geometric shapes like cones or prisms, or use fixed resolution / cylindrical shell approximation integration after acquiring the point cloud, leading to amplified errors in boundaries and concave areas. If 3D laser scanning is used, the equipment is expensive, maintenance is complex, and it requires shutdown, making continuous dynamic monitoring difficult. This application acquires point clouds in real time using a tri-vision vision system, uses B-spline interpolation to express arbitrary curved surfaces as continuous functions, and applies Simpson's rule two-dimensional integration along the first and second coordinate axes. Instantaneous volumes can be continuously output without downtime, achieving low-cost, high-precision dynamic warehouse management.

[0024] Please refer to Figure 1 This is a flowchart illustrating a non-contact method for measuring the volume of a bulk material pile, as provided in an embodiment of this application. This application provides a non-contact method for measuring the volume of a bulk material pile, which can be used to calculate the volume of bulk materials such as grain, ore, and feed formed inside a storage container. The following explanation uses grain as the bulk material pile and a grain silo as the storage container as an example, but this method is not limited to grain scenarios. The bulk material forms a geometric body with a free-form surface at the top inside the storage container. The non-contact method for measuring the volume of a bulk material pile includes steps S101-S103.

[0025] Step S101: Use a tri-vision system to acquire three-dimensional point cloud data of the top surface of the bulk material pile.

[0026] In step S101, the trinocular vision system includes three camera devices C1, C2, and C3. For example... Figure 8 As shown, the three camera devices C1, C2, and C3 are arranged in an isosceles triangle. Camera device C1, located at the lowest point, has the smallest distance to the top surface 200 of the bulk material pile, and its field of view covers the top surface 200. It also has a height difference with the other two camera devices C2 and C3, ensuring that the fields of view of the other two camera devices C2 and C3 also cover the top surface 200. The trinocular vision system simultaneously acquires three images of the top surface 200 of the bulk material pile using the three camera devices C1, C2, and C3, which are then used to generate 3D point cloud data. The three camera devices C1, C2, and C3 used in this application acquire various information such as color, texture, and shape, enabling image recognition to pre-identify pixel regions belonging to the top surface 200 of the bulk material pile from the images acquired by the camera devices C1, C2, and C3, facilitating subsequent volume calculation.

[0027] Please refer to Figure 2 This is a flowchart of step S101 provided in the embodiments of this application. Acquiring three-dimensional point cloud data of the top surface of the bulk material pile using a tri-vision vision system includes steps S1011-S1016.

[0028] Step S1011: The tri-vision system is calibrated to obtain the intrinsic parameters, extrinsic parameters, and distortion coefficients of each camera device.

[0029] In step S1011, intrinsic parameters are parameters that reflect the internal characteristics of the imaging devices C1, C2, and C3, especially parameters related to the optical systems and imaging sensors of the imaging devices C1, C2, and C3. Intrinsic parameters reflect how the imaging devices C1, C2, and C3 project points in their three-dimensional space onto the two-dimensional image plane. Extrinsic parameters reflect the position and orientation of the camera in its world coordinate system, used to define the transformation relationship between the imaging device coordinate system and the world coordinate system. The calibration of the trinocular vision system will be explained below.

[0030] First, construct any point in the three-dimensional space where any imaging device is located, and the projection relationship between corresponding pixels when that point is projected onto the pixel coordinate system of the corresponding imaging device. In this application, the projection relationship is expressed as... ,in, Represents any scaling factor parameter. Represents the augmented matrix at any point. This represents the augmentation matrix for the corresponding pixel. Represents the rotation matrix. Represents the translation vector. Indicates external reference. , indicating internal reference. Among them, ( () represents the principal point coordinates in the pixel coordinate system. This represents the scaling factor along the first axis in the pixel coordinate system. This represents the scaling factor along the second axis in the pixel coordinate system. This represents the tilt factor between the first axis and the second axis.

[0031] Then, based on the projection relationship, the homography matrix is ​​constructed. The homography matrix is ​​represented as follows: ,in, Represents the homography matrix. , These represent the first and second columns of the rotation matrix, respectively. and mutually orthogonal , , These represent the first, second, and third columns of the homography matrix, respectively. Represents any scale factor.

[0032] Next, a reference matrix and reference vectors are constructed based on the homography matrix. The reference vectors are obtained by vectorizing the reference matrix in a predetermined order. The reference matrix is ​​represented as follows: The reference vector is represented as .

[0033] Next, the reference vector is calculated based on the preset equation, and the reference matrix is ​​calculated accordingly. The preset equation is expressed as follows: ,in, .

[0034] Next, the scaling factor, intrinsic parameters, and extrinsic parameters are obtained based on the reference matrix. The scaling factor is expressed as: ; Internal references are represented as follows: ; ; ; ; .

[0035] External parameters are represented as: ; ; × ; .

[0036] Finally, construct any point in the three-dimensional space where the remaining imaging devices are located, and the projection relationship between corresponding pixels when any point is projected onto the pixel coordinate system of the corresponding imaging device, until the intrinsic and extrinsic parameters of each imaging device C1, C2, and C3 are obtained. The following will further explain how to obtain the distortion coefficients of each imaging device C1, C2, and C3.

[0037] First, multiple marker points are pre-determined from each image, and the pixel coordinates of each marker point within the corresponding image are obtained to construct a corresponding positional relationship function. This positional relationship function reflects the relationship between a marker point and its corresponding ideal coordinates.

[0038] Then, the distortion coefficients are calculated based on several positional relationship functions. These distortion coefficients include radial distortion coefficients and tangential distortion coefficients. The expression for each positional relationship function is as follows: , in, , , , These are the radial distortion coefficients, , These are the tangential distortion coefficients, This represents the pixel coordinates of each marker point.

[0039] Step S1012: Based on the intrinsic parameters, extrinsic parameters, and distortion coefficients, perform distortion correction on the three images to obtain three distortion-free images.

[0040] In step S1012, when the three-dimensional coordinates of each point in each image are obtained, the ideal coordinates of each point in the image are obtained according to the positional relationship function and the calculated distortion coefficient, thus forming a distortion-free image of the corresponding image.

[0041] Step S1013: Take any two of the three distortion-free images as image pairs, and perform epipolar correction on each image pair to obtain three corrected image pairs.

[0042] Please refer to Figure 3 The flowchart below shows step S1013, which is provided in the embodiment of this application. Taking any two of the three distortion-free images as image pairs, epipolar correction is performed on each image pair to obtain three pairs of corrected image pairs, including steps S10131-S10132.

[0043] Step S10131: Using intrinsic parameters, extrinsic parameters, and distortion coefficients, calculate the relative rotation matrix and relative translation vector between the three pairs of camera devices.

[0044] In step S10131, each pair of camera devices consists of two of the three camera devices C1, C2, and C3, forming a binocular vision system. That is, a tri-camera vision system can construct three binocular vision systems. For example, in this application, two camera devices C1 and C2 constitute one binocular vision system, two camera devices C1 and C3 constitute two binocular vision systems, and two camera devices C2 and C3 constitute a third binocular vision system. In this application, based on the extrinsic and intrinsic parameters of the two camera devices in any binocular vision system, the relative rotation matrix and relative translation vector of any binocular vision system are calculated until the relative rotation matrix and relative translation vector of each binocular vision system are obtained. The expression for the relative rotation matrix is: , Indicates the first The camera device is relative to the first The relative rotation matrix of each camera device, Indicates the first Rotation matrix of each camera device, Indicates the first The expressions for the rotation matrix and relative translation vector of each camera device are as follows: .in, , , Indicates the first The translation vector of each camera device. Indicates the first The translation vector of each camera device. Indicates the first The camera device is relative to the first The relative translation vector of each camera device.

[0045] Taking two camera devices C1 and C2 as an example, the relative rotation matrix in their binocular vision system is: Let represent the rotation matrix of camera C2 relative to camera C1, C2, and C3, with camera devices C1, C2, and C3 as the world coordinate system; the relative translation vector is . Let represent the translation vector of camera C2 relative to camera C1, C2, and C3. The relative rotation matrix and relative translation vector reflect the relative positions and orientations of camera C1 and C2 in the world coordinate system. In other words, when the relative rotation matrix and relative translation vector of each camera C1, C2, and C3 within its binocular vision system are obtained, the positions and orientations of the three camera devices C1, C2, and C3 can be determined.

[0046] Step S10132: Based on the relative rotation matrix and the relative translation vector, the distortion-free image corresponding to each pair of camera devices is mapped to a corrected image that corresponds in the first coordinate axis direction and whose epipolar lines coincide, so as to obtain three pairs of corrected image pairs.

[0047] In step S10132, for the distortion-free images corresponding to the two imaging devices, the two distortion-free images are mapped to the same epipolar plane using the relative rotation matrix and relative translation vector of the two imaging devices, and the corresponding epipolar lines are aligned in the first coordinate axis direction, forming a pair of corrected images that correspond in the first coordinate axis direction and whose epipolar lines coincide. This application performs this process sequentially on three pairs of imaging devices to obtain three pairs of corrected image pairs with aligned epipolar lines. The first coordinate axis direction will be described in detail below.

[0048] Step S1014: Based on the intrinsic and extrinsic parameters, perform stereo matching on each pair of corrected images to obtain disparity information.

[0049] Please refer to Figure 4 The flowchart below shows step S1014, a sub-step provided in the embodiments of this application. Based on intrinsic and extrinsic parameters, stereo matching is performed on each pair of corrected images to obtain disparity information, including steps S10141-S10143.

[0050] Step S10141: Based on the intrinsic and extrinsic parameters, calculate the matching cost for each pair of corrected images along the first coordinate axis to generate the corresponding initial disparity map.

[0051] In step S10141, for each pair of corrected images, a cost function is used to calculate the matching cost pixel by pixel along the first coordinate axis. In this application, the cost function can be Census transform, SAD, or normalized cross-correlation, etc., and is performed separately for each pair of corrected images to generate three initial disparity maps. The initial disparity map is a two-dimensional matrix with the same size as the corrected image, and each element stores a horizontal offset with a preset pixel precision; a larger value indicates a closer depth.

[0052] Step S10142: Based on the remaining camera devices that did not participate in the formation of the corresponding correction image pairs, perform consistency verification on each initial disparity map to remove mismatched regions from each initial disparity map.

[0053] In step S10142, for a pair of corrected images, the remaining cameras among the three cameras C1, C2, and C3 (excluding the two cameras corresponding to the two distortion-free images) are used as the other cameras. The corresponding initial disparity map is back-projected onto the image space of this remaining camera, and the reprojection error of the three is compared. If the disparity difference of pixels in the three images exceeds a preset threshold, it is marked as a mismatch and discarded; only the disparity values ​​that are consistent across the three cameras are retained to form a reliable disparity mask.

[0054] Step S10143: Fuse the initial disparity maps after removal to obtain disparity information.

[0055] In step S10143, pixels that pass the consistency test are fused into a disparity map as disparity information by weighted averaging of trioptic reprojection error.

[0056] Step S1015: Calculate the initial three-dimensional coordinates of the top surface of the bulk material pile based on the parallax information, intrinsic parameters, and extrinsic parameters.

[0057] In step S1015, the disparity information after trio-view consistency verification is combined with the intrinsic parameter matrix and relative extrinsic parameters of the corresponding camera device, and the disparity value of each pixel is converted into three-dimensional coordinates in the world coordinate system using the principle of triangulation. This application calculates the disparity information sequentially for three pairs of binocular images and unifies the resulting three-dimensional coordinates to the same world coordinate system to form an initial three-dimensional coordinate system covering the entire top surface 200 of the bulk material pile.

[0058] Step S1016: Unify the initial three-dimensional coordinates to the same world coordinate system to form three-dimensional point cloud data.

[0059] The following explains how to calculate the initial 3D coordinates of the top surface 200 of the bulk material pile based on parallax information, intrinsic parameters, and extrinsic parameters, and how to unify these initial 3D coordinates to the same world coordinate system to form 3D point cloud data: First, obtain the homogeneous pixel coordinates of each point on the top surface 200 of the bulk material pile from any image. Then, based on the homogeneous pixel coordinates and projection relationships, calculate the 3D coordinates of each point on the top surface 200 of the bulk material pile in any image using a trinocular vision system as the initial 3D coordinates. When obtaining the 3D coordinates of each point on the surface in each image, unify the 3D coordinates of each point in each image to the world coordinate system of one of the cameras to determine the 3D coordinates of each point on the surface in the world coordinate system. The homogeneous pixel coordinates are represented as follows: , Adding a constant of 1 to the x and y coordinates of a point in the image in the pixel coordinate system converts the two-dimensional coordinates into a homogeneous form, facilitating matrix transformation operations. The expression for the three-dimensional point cloud data is as follows: ,in, This represents the coordinate of the third axis of each point on a surface in any image, in the pixel coordinate system of the corresponding camera device. Denotes the projection matrix, and ,in, Indicates the first The intrinsic parameter matrix of each camera device, Indicates the first Rotation matrix of each camera device, Indicates the first The translation vector of each camera device. Represents the homogeneous three-dimensional coordinates of each point on the surface, where, These represent the X, Y, and Z axes in the world coordinate system. In this application, the first, second, and third axes constitute different axes of the pixel coordinate system of the corresponding imaging device. For example, the first, second, and third axes can be the X, Y, and Z axes of the pixel coordinate system, respectively.

[0060] It is understandable that for the three camera devices C1, C2, and C3, since the binocular vision system formed by two camera devices C1 and C2, and the binocular vision system formed by two camera devices C1 and C3, both use camera devices C1, C2, and C3 as the world coordinate system, while the binocular vision system formed by two camera devices C2 and C3 uses camera device C2 as the world coordinate system, this application only needs to transform the three-dimensional coordinates of each point on the surface using camera device C2 as the world coordinate system to the three-dimensional coordinates of each point on the surface using camera devices C1, C2, and C3 as the world coordinate system to determine the three-dimensional coordinates of each point on the surface in a unified world coordinate system.

[0061] Step S102: Perform B-spline interpolation on the three-dimensional point cloud data to obtain a continuous surface function about the top surface of the bulk material pile within the horizontal projection domain of the top surface of the bulk material pile.

[0062] In step S102, B-spline interpolation is a piecewise polynomial approximation method. Through a linear combination of low-order basis functions, it can generate continuous, differentiable, and curvature-continuous surfaces on arbitrarily dense control point grids, thus avoiding the oscillations at boundaries inherent in traditional polynomial interpolation. In this application, the B-spline basis functions include a first basis function and a second basis function. The horizontal projection domain can be the xOy plane (i.e., the plane where the z-axis value is 0). Correspondingly, the first coordinate axis direction can be the x-axis direction, and the second coordinate axis direction can be the y-axis direction. The continuous surface function is continuously differentiable throughout the entire horizontal projection domain and can be directly used for subsequent integration using Simpson's rule to calculate the volume of arbitrarily complex surfaces.

[0063] Please refer to Figure 5 The flowchart below shows step S102, a sub-step provided in the embodiments of this application. Steps S1021-S1022 involve performing B-spline interpolation on the three-dimensional point cloud data to obtain a continuous surface function about the top surface of the bulk material pile within the horizontal projection domain of the top surface.

[0064] Step S1021: Rasterize the 3D point cloud data into a regular grid within the horizontal projection domain to obtain multiple grid control points.

[0065] In step S1021, within the horizontal projection domain (xoy plane), the three-dimensional point cloud of the top surface 200 of the bulk material pile is uniformly divided into equidistant rectangular grids, with each grid node serving as a grid control point. Each grid control point includes its planar coordinates and its height value on the top surface 200 of the bulk material pile. The planar coordinates are composed of different coordinate axis directions. In this application, the grid control point is represented as follows: , Represents planar coordinates, This represents the height value of the top surface of the bulk material pile at coordinate 200 in the plane.

[0066] Step S1022: Using B-spline basis functions, interpolation is performed sequentially along the first coordinate axis and the second coordinate axis to generate a continuous surface function.

[0067] In step S1022, the height values ​​of the control points are interpolated row by row along the first coordinate axis using B-spline basis functions, and then interpolated column by column along the second coordinate axis, finally obtaining a continuous surface function that is continuous, differentiable, and has continuous curvature throughout the entire horizontal projection domain.

[0068] Figure 6The flowchart below shows step S1022, which is provided in the embodiment of this application. Using B-spline basis functions, interpolation is performed sequentially along the first coordinate axis and the second coordinate axis to generate a continuous surface function, including steps S10221-S10222.

[0069] Step S10221: Interpolate the height values ​​of the grid control points along the first coordinate axis using the first basis function to obtain the intermediate surface function.

[0070] In step S10221, the first basis function is expressed as: , in, Indicates the direction of the first coordinate axis The first order One B-spline basis function, This indicates the current coordinate value in the direction of the first coordinate axis. Indicates the first The coordinate values ​​of each grid control point along the first coordinate axis.

[0071] The intermediate surface function is represented as: , in, This represents the total number of grid control points along the first coordinate axis. The planar coordinates of the grid control points are: The height value at 200 on the top surface of the bulk material pile.

[0072] Step S10222: Interpolate the intermediate surface function along the second coordinate axis using the second basis function to generate a continuous surface function.

[0073] In step S10222, the second basis function is expressed as: , in, Indicates the direction of the second coordinate axis The first order One B-spline basis function, This indicates the current coordinate value in the direction of the second coordinate axis. Indicates the first The coordinate values ​​of each grid control point along the second coordinate axis.

[0074] The continuous surface function is represented as: , in, This represents the total number of grid control points along the second coordinate axis.

[0075] Step S103: In the horizontal projection domain, Simpson's rule is used to perform two-dimensional integration on the continuous surface function along different coordinate axis directions to obtain the instantaneous volume of the bulk material pile.

[0076] In step S103, the different coordinate axis directions include the first coordinate axis direction and the second coordinate axis direction. The first coordinate axis direction and the second coordinate axis direction are perpendicular to each other in the horizontal projection domain. In this application, the continuous surface function is divided into multiple Simpson integral units 1 equidistant from the total number of grid control points in the horizontal projection domain along the first coordinate axis direction and the second coordinate axis direction. Points of different categories in each Simpson integral unit 1 are weighted according to Simpson weights. The instantaneous volume is obtained by multiplying the surface height value, the weight value, and the unit area.

[0077] Please refer to Figure 7 The flowchart below shows step S103, which is a sub-step provided in the embodiment of this application. Steps S1031-S1033 involve performing two-dimensional integration of the continuous surface function along different coordinate axes within the horizontal projection domain using Simpson's rule to obtain the instantaneous volume of the bulk material pile.

[0078] Step S1031: Based on the total number of grid control points along the first coordinate axis and the total number of grid control points along the second coordinate axis, divide the horizontal projection domain into equidistant grid segments along the first and second coordinate axes to form Simpson integral units.

[0079] In step S1031, within the horizontal projection domain, the domain is divided equidistantly along both coordinate axes, with the total number of grid control points along the first coordinate axis as the number of segments and the total number of grid control points along the second coordinate axis as the number of columns, to form Simpson integral units 1. In this application, the total number of grid control points along the first coordinate axis is... The total number of grid control points along the second coordinate axis The number of segments corresponds to The number of columns corresponds to .like Figure 9 As shown, assuming the horizontal projection domain is rectangular, its range in the first coordinate axis direction (X-axis direction) is [ , ](in The left boundary It is the right boundary, and < The range of the second coordinate axis direction (Y-axis direction) is [ , ](in The lower boundary is... The upper boundary is, and < Since the bottom surface 200a of the bulk material pile is located within the horizontal projection domain, the step size in the direction of the first coordinate axis is... The step size in the direction of the second coordinate axis is Therefore, the area of ​​Simpson integral unit 1 is correspondingly... .

[0080] Step S1032: Assign corresponding weights to each Simpson integral unit along the first coordinate axis and the second coordinate axis according to Simpson's rule, so that each point in the corresponding Simpson integral unit obtains the corresponding weight value.

[0081] In step S1032, each point includes four corner points 11, four edge midpoints 12, and one interior point. The four corner points 11 are located at the four corners of the corresponding Simpson integration unit 1 within the horizontal projection domain; the edge midpoints 12 are located at the midpoints of the edges corresponding to each corner point 11; and the interior point is located at the geometric center of the corresponding Simpson integration unit 1. Points of the same category have equal weight values, while points of different categories have different weight values. In this application, weights are assigned to the nine points within each Simpson integration unit 1 according to Simpson's rule. Specifically, the coordinates of each point are represented as follows: The weight value of this point is expressed as .in, and These are the weight values ​​of the point in the first coordinate axis direction and the second coordinate axis direction, respectively. More specifically, for ,when hour, The value is 1; when When it is an odd number, The value is 4; when When it is even, The value is 2. For ,when hour, The value is 1; when When it is an odd number, The value is 4; when When it is even, The value is 2.

[0082] Furthermore, for Simpson integration units 1 outside the bottom surface 200a, the weight value is set to 0, and they are not included in the instantaneous volume accumulation calculation. For Simpson integration units 1 within the bottom surface 200a but not completely covered, only the corner points 11, edge midpoints 12, and internal points 13 located within the bottom surface 200a retain the corresponding weight values, while the weight values ​​of the remaining parts are set to 0, and the corresponding unit area is calculated according to the actual area located within the bottom surface 200a to ensure the integration accuracy at the boundary.

[0083] Step S1033: Multiply the surface height value, the weight value of each point, and the area of ​​each Simpson integral unit and sum them up to obtain the instantaneous volume.

[0084] In step S1033, the instantaneous volume is expressed as This application multiplies the surface height value, corresponding weight value, and cell area of ​​each of the 9 points within each Simpson integration cell 1 point by point and then sums them up to complete the bidirectional integration of the entire horizontal projection domain. The summed result is the instantaneous volume. For cylinders, cones, or any cubic surface, the error can converge rapidly as the mesh is refined, realizing continuous and high-precision dynamic volume monitoring under a single trinocular vision system.

[0085] Please refer to Figure 10 This is a structural block diagram of a non-contact bulk material pile volume measurement device provided in an embodiment of this application. This application also provides a non-contact bulk material pile volume measurement device. The measurement device includes three camera devices C1, C2, and C3, and a main control device 100. The three camera devices C1, C2, and C3 are used to construct a tri-vision system. The main control device 100 can be a computer device.

[0086] Please refer to Figure 11 This is a schematic diagram of the internal structure of the main control device provided in the embodiments of this application.

[0087] like Figure 11 As shown, the main control device 100 includes a memory 901 and a processor 902. The processor 902 is used to run computer program instructions in the memory 901 to implement a non-contact method for measuring the volume of bulk material piles.

[0088] The memory 901 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 901 can be an internal storage unit of a computer device, such as a hard disk. In other embodiments, the memory 901 can be an external storage device of a computer device, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, etc., configured in the computer device. Furthermore, the memory 901 can include both internal and external storage units of a computer device. The memory 901 can be used not only to store application software and various types of data installed on the computer device, such as code for non-contact bulk material stack volume measurement methods, but also to temporarily store data that has been output or will be output.

[0089] Furthermore, the main control device 100 also includes a bus 903. The bus 903 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. This bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 11 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0090] Furthermore, the main control device 100 may also include a display component 904. The display component 904 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an organic light-emitting diode (OLED) touch screen, etc. The display component 904 may also be appropriately referred to as a display device or display unit, used to display information processed in the main control device 100 and to display a visual user interface.

[0091] Furthermore, the main control device 100 may also include a communication component 905. The communication component 905 may optionally include a wired communication component and / or a wireless communication component (such as a Wi-Fi communication component, a Bluetooth communication component, etc.), which is typically used to establish a communication connection between the main control device 100 and other computer devices.

[0092] Figure 11 Only a portion of the main control device 100, which includes some components and a method for measuring the volume of non-contact bulk material piles, is shown. Those skilled in the art will understand that... Figure 11 The structure shown does not constitute a limitation on the main control device 100, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0093] In the above embodiments, the implementation can be achieved, in whole or in part, through software, hardware, or any combination thereof. When implemented using software, it can be implemented, in whole or in part, in the form of a computer program product.

[0094] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to embodiments of the present invention is generated. The computer device may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state disk (SSD)).

[0095] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0096] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units through some interfaces, and may be electrical, mechanical, or other forms.

[0097] The unit described as a separate component may or may not be physically separate. The component shown as a unit may or may not be a physical unit; that is, it may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0098] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist independently, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0099] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes: USB flash drives, portable hard disks, read-only storage media (ROM), random access storage media (RAM), magnetic disks, optical disks, and other media capable of storing program code.

[0100] The beneficial effects of the above embodiments are as follows: by acquiring images in real time and generating three-dimensional point cloud data through a tri-vision vision system, continuous dynamic monitoring of volume changes during material feeding and discharging is realized, overcoming the limitation of traditional methods that require machine shutdown for measurement; by using B-spline interpolation to express complex surfaces as continuous functions, the ability to describe boundaries and concave regions is significantly improved, avoiding errors caused by the simplification of regular geometry; and by using Simpson's rule two-dimensional integrals along the first and second coordinate axes, the accuracy of volume calculation is further improved, making the results closer to the true values; this scheme uses only three camera devices, significantly reducing hardware costs, and the system has no moving parts, making maintenance easier in dusty environments. Overall, it achieves low-cost, high-precision, and easy-to-maintain dynamic monitoring of bulk material pile volume.

[0101] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

[0102] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0103] The above-listed examples are merely preferred embodiments of this application and should not be construed as limiting the scope of this application. Therefore, any equivalent variations made in accordance with the claims of this application shall still fall within the scope of this application.

Claims

1. A method for measuring the volume of a non-contact bulk material pile, characterized in that, The measurement method includes: A tri-vision system was used to acquire three-dimensional point cloud data of the top surface of the bulk material pile; B-spline interpolation is performed on the three-dimensional point cloud data to obtain a continuous surface function about the top surface of the bulk material pile within the horizontal projection domain of the top surface of the bulk material pile. Within the horizontal projection domain, the continuous surface function is integrally integrated in two dimensions using Simpson's rule along different coordinate axis directions to obtain the instantaneous volume of the bulk material pile. The different coordinate axis directions include a first coordinate axis direction and a second coordinate axis direction, which are perpendicular to each other within the horizontal projection domain.

2. The measurement method as described in claim 1, characterized in that, The trinocular vision system includes three camera devices arranged in an isosceles triangle. The camera device located at the lowest point has the smallest distance from the top surface of the bulk material pile, and its field of view can cover the top surface of the bulk material pile. It also has a height difference from the other two camera devices. The trinocular vision system simultaneously acquires three images of the top surface of the bulk material pile through the three camera devices, and uses these three images to generate the three-dimensional point cloud data.

3. The measurement method as described in claim 2, characterized in that, A three-dimensional point cloud data of the top surface of the bulk material pile is acquired using a tri-vision vision system, including: The trinocular vision system is calibrated to obtain the intrinsic parameters, extrinsic parameters, and distortion coefficients of each camera device; Based on the distortion coefficients, the three images are distorted to obtain three distortion-free images; Using any two of the three distortion-free images as image pairs, epipolar correction is performed on each image pair to obtain three corrected image pairs. Based on the intrinsic and extrinsic parameters, stereo matching is performed on each pair of corrected images to obtain disparity information; Based on the parallax information, intrinsic parameters, and extrinsic parameters, calculate the initial three-dimensional coordinates of the top surface of the bulk material pile; The initial three-dimensional coordinates are unified to the same world coordinate system to form the three-dimensional point cloud data.

4. The measurement method as described in claim 3, characterized in that, Using any two of the three distortion-free images as image pairs, epipolar correction is performed on each image pair to obtain three corrected image pairs, including: Using the intrinsic and extrinsic parameters, the relative rotation matrix and relative translation vector between the three pairs of camera devices are calculated, where each pair of camera devices consists of two of the three camera devices; Based on the relative rotation matrix and the relative translation vector, the distortion-free image corresponding to each pair of camera devices is mapped to a corrected image that corresponds in the direction of the first coordinate axis and whose epipolar lines coincide, so as to obtain the three pairs of corrected image pairs.

5. The measurement method as described in claim 3, characterized in that, Based on the intrinsic and extrinsic parameters, stereo matching is performed on each corrected image pair to obtain disparity information, including: Based on the intrinsic and extrinsic parameters, the matching cost is calculated for each pair of corrected images along the first coordinate axis, and a corresponding initial disparity map is generated. Based on the remaining camera devices that did not participate in the formation of the corresponding corrected image pairs, the consistency of each initial disparity map is verified in order to remove mismatched regions from each initial disparity map; The disparity information is obtained by fusing the initial disparity maps after each rejection.

6. The measurement method as described in claim 1, characterized in that, B-spline interpolation is performed on the three-dimensional point cloud data to obtain a continuous surface function about the top surface of the bulk material pile within the horizontal projection domain of the top surface of the bulk material pile, including: Within the horizontal projection domain, the three-dimensional point cloud data is rasterized into a regular grid to obtain multiple grid control points. Each grid control point includes planar coordinates and its height value on the top surface of the bulk material pile. The planar coordinates are composed of the different coordinate axis directions. Using B-spline basis functions, interpolation is performed sequentially along the first coordinate axis and the second coordinate axis to generate the continuous surface function.

7. The measurement method as described in claim 6, characterized in that, The B-spline basis functions include a first basis function and a second basis function; using the B-spline basis functions, interpolation is performed sequentially along the first coordinate axis and the second coordinate axis to generate the continuous surface function, including: The height values ​​of the grid control points are interpolated along the first coordinate axis using the first basis function to obtain the intermediate surface function. The first basis function is expressed as follows: ,in, Indicates the direction of the first coordinate axis The first order A B-spline basis function, This represents the current coordinate value along the first coordinate axis. Indicates the first The coordinate values ​​of each grid control point along the first coordinate axis; the intermediate surface function is expressed as... ,in, This represents the total number of grid control points along the first coordinate axis. The planar coordinates of the grid control points are: The height value at the top surface of the bulk material pile; The continuous surface function is generated by interpolating the intermediate surface function along the second coordinate axis using the second basis function. The second basis function is expressed as follows: ,in, Indicates the direction of the second coordinate axis The first order A B-spline basis function, This indicates the current coordinate value in the direction of the second coordinate axis. Indicates the first The coordinate values ​​of each grid control point along the second coordinate axis; the continuous surface function is expressed as... ,in, This represents the total number of grid control points along the second coordinate axis.

8. The measurement method as described in claim 1, characterized in that, Within the horizontal projection domain, the continuous surface function is integrated in two dimensions using Simpson's rule along different coordinate axes to obtain the instantaneous volume of the bulk material pile, including: Based on the total number of grid control points along the first coordinate axis and the total number of grid control points along the second coordinate axis, equidistant grid segments are divided within the horizontal projection domain along the first and second coordinate axis directions to form Simpson integral units. According to Simpson's rule, each Simpson integral unit is assigned a corresponding weight along the first coordinate axis and the second coordinate axis, so that each point in the corresponding Simpson integral unit obtains the corresponding weight value. The instantaneous volume is obtained by multiplying the surface height value, the weight value of each point, and the area of ​​each Simpson integral unit, and then summing them up.

9. The measurement method as described in claim 8, characterized in that, Each point includes four corner points, four midpoints of edges, and one interior point. The four corner points are located at the four corners of the corresponding Simpson integral unit within the horizontal projection domain. The midpoints of edges are located at the midpoints of the edges connected to each corner point. The interior point is located at the geometric center of the corresponding Simpson integral unit. Points of the same category have equal weight values, while points of different categories have different weight values.

10. A non-contact device for measuring the volume of bulk material piles, characterized in that, The measuring device includes: Three camera devices are used to construct a trinocular vision system; and The main control device, which is communicatively connected to the three camera devices, includes: Memory, used to store computer programs; A processor for executing the computer program to implement the non-contact method for measuring the volume of a bulk material stack as described in any one of claims 1-9.

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